Detection of Skin Cancer Using Deep Learning Approach

Abstract

Critical research is presently being done in the field of computer visions to classify and identify skin cancer. Several deep convolutional neural networks were used by researchers to enhance the performance of the current systems. There have been several efforts made in the past to identify skin cancer. To increase performance and accuracy, many researchers employ a variety of efficient procedures. In this thesis project, we are attempting to build a model for identifying skin cancer based on method (DenseNet 121). For training and testing purposes in detecting skin cancer, we employed a dataset. Our suggested model has a 92% accuracy rate.